SUMSearch and TRIP database are meta search engines for searching clinical evidence. This article introduces major contents and search methods of the SUMSearch and TRIP database, so as to provide quick search resources and technical help for evidence-based practice.
ObjectiveTo analyze the relationship between occupation and tumor characteristics of colorectal patients served by West China Hospital of Sichuan University as a regional center in the current version of Database from Colorectal Cancer (DACCA). MethodsThe data of DACCA was updated on January 5, 2022. All data items included occupation, tumor morphology, distance of tumor from dentate line, tumor site, properties of tumor, differentiation degree, postoperative complex physiological index (CPI) stage, tumor comorbidities, tumor location, and tumor occurrence. According to the 2015 edition of the Occupational Classification of the People’s Republic of China, the occupational parameters of patients in this study were divided into three groups: Mental workers, physical workers and unemployed residents. ResultsThe DACCA database was filtered according to the conditions, obtaining 3 215 valid data. In terms of tumor complications, there were significant differences in the proportion of tumor bleeding, perforation grade, mechanical intestinal obstruction degree and pain degree among the different occupational groups (P<0.05). There were no significant difference in the ratio of edema degree and intussusception of tumor site among the different occupational groups (P>0.05). There were no significant difference in the composition ratio of tumor differentiation degree, tumor occurrence, tumor orientation and tumor morphology among the different occupational groups (P>0.05). The composition ratio of CPI staging of colorectal cancer, the distance between tumor and dentate line, the composition ratio of different tumor pathological properties, and the composition ratio of tumor located in rectum and colon were statistically significant (P<0.05). ConclusionPreoperative tumor characteristics of patients with colorectal cancer are associated with various occupations. In patients with rectal cancer, the distance from the dentate line to the physical work of the tumor is smaller, lower site, some tumor complications are more severe, and the stage is relatively later.
ObjectiveTo analyze the details and efficacy of neoadjuvant therapy of colorectal cancer in the current version of Database from Colorectal Cancer (DACCA).MethodsThe DACCA version selected for this data analysis was the updated version on July 28th, 2020. The data items included “planned strategy of neoadjuvant therapy” “compliance of neoadjuvant therapy”, and “cycles of neoadjuvant therapy”. Item of “planned strategy of neoadjuvant therapy” included “accuracy of neoadjuvant therapy” and “once included in researches”. Item of “the intensity of neoadjuvant therapy” included “chemotherapy” “cycles of neoadjuvant therapy” “targeted drugs”, and “neoadjuvant radiotherapy”. Item of “effect of neoadjuvant therapy” included CEA value of “pre-neoadjuvant therapy” and “post-neoadjuvant therapy”“variation of tumor markers” “variation of symptom” “variation of gross” “variation of radiography”, and tumor regression grade (TRG). The selected data items were statistically analyzed.ResultsThe total number of medical records (data rows) that met the criteria was 7 513, including 2 539 (33.8%) valid data on the “accuracy of neoadjuvant therapy”, 498 (6.6%) valid data on “once included in researches”, 637 (8.5%) valid data on the “compliance of neoadjuvant therapy”, 2 077 (27.6%) valid data on “neoadjuvant chemotherapy”, 614 (8.2%) valid data on “cycles of neoadjuvant therapy”, 455 (6.1%) valid data on “targeted drugs”, 135 (1.8%) valid data on “neoadjuvant radiotherapy”, 5 022 (66.8%) valid data on “pre-neoadjuvant therapy CEA value”, 818 (10.9%) valid data on “post-neoadjuvant therapy CEA value ”, 614 (8.2%) valid data on “variation of tumor marker”, 464 (6.2%) valid data on “variation of symptom”, 478 (6.4%) valid data on “variation of gross”, 492 (6.5%) valid data on “variation of radiography”, and 459 (6.1%) valid data on TRG. During the correlation analysis, it appeared that “variation of tumor marker” and “variation of gross” (χ2=6.26, P=0.02), “variation of symptom” and “variation of gross”, “radiography” and TRG (χ2=53.71, P<0.01; χ2=38.41, P<0.01; χ2=8.68, P<0.01), “variation of gross” and “variation of radiography”, and TRG (χ2=44.41, P<0.01; χ2=100.37, P<0.01), “variation of radiography” and TRG (χ2=31.52, P<0.01) were related with each other.ConclusionsThe protocol choosing of neoadjuvant therapy has a room for further research and DACCA can provide data support for those who is willing to perform neoadjuvant therapy. The efficacy indicators of neoadjuvant therapy have association with each other, the better understand of it will provide more valuable information for the establishment of therapeutic prediction model.
ObjectivesTo develop a real-world-data-based monitoring system for diagnostic large medical equipment, and to use PET/CT as a carrier for validation. MethodsWe used literature survey, site investigation, and two-rounds of modified Delphi methods to develop the indicator system, and used the analytic hierarchy process method to determine the weight of each indicator. We collected real-world PET/CT data from four tertiary hospitals from July to December 2022, and monitored the use of PET/CT in each hospital. ResultsQuestionnaire recovery rates of 2 rounds were 100% and 88%, respectively, the expert authority coefficient was greater than 0.70, and the coordination coefficients of experts in the total index were 0.307 and 0.471 (P<0.001). A three-level indicator system was established to monitor the use of large medical equipment, with three first-level indicators (clinical use, implementation, and other efficiencies), eight second-level indicators, and 15 third-level indicators. Empirical experiment found different hospitals vary in efficiency (of clinical use), staff status, and economic and research efficiency, while remained similar in other indicators. ConclusionWe developed a monitoring system for diagnostic large medical equipment based on real-world data, and used PET/CT as a carrier for validation. These findings provided theoretical and empirical foundations for the management of diagnostic large medical equipment in China.
Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. ResultsTaking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.
ObjectiveTo analyze the neoadjuvant therapy of colorectal cancer in this center in the background of real world data by studying Database from Colorectal Cancer (DACCA) in West China Hospital of Sichuan University.MethodsData was selected from DACCA who was updated on August 15, 2019. After deleting duplicate value, patients whose tumor location and tumor pathologic characteristic showed colon or rectum, as well as adenocarcinoma, mucinous adenocarcinoma, and signet ring cell carcinoma were enrolled.ResultsThere were 2 783, 2 789, 2 790, 2 811, 4 148,3 824, 4 191, 3 676, 4 090, and 499 valid data of T, N, and M stages, clinical stages, tumor site, distance from tumor to anal dentate line, tumor pathologic characteristics, degree of tumor differentiation, neoadjuvant therapy, and compliance, respectively. There were 1 839 lines that " nature of the tumor pathology” was not empty and neoadjuvant scheme for the pure chemotherapy, radiotherapy alone or radiation, and chemotherapy, including 50 lines of signet ring cell carcinoma (2.7%), 299 lines of mucous adenocarcinoma (16.3%), 1 490 lines of adenocarcinoma (81.0%), various kinds of pathology in selection of neoadjuvant therapy difference was statistically significant (χ2=9.138, P=0.041). Except for the data lines with null value in the column of " operation date”, there were 2 234 (82.1%) and 486 (17.9%) effective data lines of " recommended” and " not recommended” for the use of neoadjuvant therapy, respectively. In the years with a large amount of data, among the patients who completed neoadjuvant therapy, the proportion of patients meeting the recommended indications was 27.4%–67.6%, with an average of 47.4%. Patients who did not meet the recommended indications but were recommended (off-label use) accounted for 7.3%–70.0%, with an average of 39.8%. According to regression analysis, the proportion in line with the recommendation (\begin{document}$\hat y $\end{document}=–0.032 5x+66.003 2, P=0.020) varies with the year, and the overall trend shows a gradual decline. The proportion of the use of super indications (\begin{document}$\hat y $\end{document}=–0.054 5x+110.174 6, P=0.002) changed with the year, and the overall trend showed a decline. A total of 1 161 valid data with non-null values of " eoadjuvant therapy regimen” and " recommended or not recommended” showed statistically significant difference in the use rate of neoadjuvant therapy among patients with different recommendation groups (χ2=9.244, P=0.002). " Patient compliance” was shown as " active cooperation” and " passive acceptance”, and " neoadjuvant therapy” was shown as " radiotherapy alone”" chemotherapy alone”, and " chemoradiotherapy” were 470 lines. There was no statistically significant difference in neoadjuvant therapy between patients receiving active and passive treatment (χ2=0.537, P=0.841). The effective data of clinical remission degree meeting the research conditions were 388 lines, including 121 lines of complete response (31.2%), 180 lines of partial response (46.4%), 79 lines of stable disease (20.4%), and 8 lines of progressive disease (2.1%). There was no statistically significant difference in clinical response degree among patients with different neoadjuvant therapy (H=0.435, P=0.783). There were 346 lines with effective data of pathologic tumor regression grade (TRG) meeting the study conditions, including 47 lines with TRG0 (13.6%), 39 lines with TRG1 (11.3%), 180 lines with TRG2 (52.0%), and 80 lines with TRG3 (23.1%). There was no statistical difference in the degree of TRG among patients with different neoadjuvant therapy (H=1.816, P=0.518).ConclusionsThe real world study reflects that in the western regional medical center, the demand for neoadjuvant therapy among the patients with colorectal cancer covered is huge. Although the implementation of neoadjuvant therapy is greatly influenced by the doctor’s recommendation behavior, the selection and recommendation of neoadjuvant therapy according to some specific clinical application guidelines are not fully met. The impact of more behavioral factors requires further in-depth analysis and research.
The use of repeated measurement data from patients to improve the classification ability of prediction models is a key methodological issue in the current development of clinical prediction models. This study aims to investigate the statistical modeling approach of the two-stage model in developing prediction models for non-time-varying outcomes using repeated measurement data. Using the prediction of the risk of severe postpartum hemorrhage as a case study, this study presents the implementation process of the two-stage model from various perspectives, including data structure, basic principles, software utilization, and model evaluation, to provide methodological support for clinical investigators.
Along with the development of computer technologies and digitization of human body' s information, the digital human entered into a new stage of modelling physical features from the stage of reconstructing anatomical structures. By summarizing domestic and abroad relevant documents, we in this paper present the general scheme of digital human and the location of physical human as well as its conception and applied value. We especially analyze the modeling process of physical human, core technologies and its research and applications in four main fields: electromagnetic radiation, ultrasound propagation, bioimpedance measurements and biomechanical analysis. We also analyze and summarize existing problems of present physical human model and point out the future development trends of physical human.
Given the growing importance of real-world data (RWD) in drug development, efficacy evaluation, and regulatory decision-making, establishing a scientific and systematic data quality regulatory framework has become a strategic priority for global pharmaceutical regulatory authorities. This paper analyzed the EU's advanced practices in RWD quality regulation, compared the RWD quality regulatory systems of China and the EU, and aimed to derive implications for enhancing China's own framework. The EU has made significant progress by promoting the interconnection, intercommunication, and efficient utilization of data resources, implementing a collaborative responsibility mechanism spanning the entire data lifecycle, developing a standardized, tool-based quality assessment system, and facilitating international cooperation and alignment of rules. While China has established an initial regulatory system for RWD quality, it still confronts challenges such as unclear mechanisms for data acquisition and utilization, underdeveloped operational standards, and unclear responsibility delineation. In contrast, by adapting relevant EU experience, China can refine its regulatory framework, establish mechanisms for the interconnection, intercommunication, and efficient utilization of RWD, develop more practical quality assessment toolkits, improve the lifecycle responsibility-sharing mechanism, and promote the alignment of RWD quality regulation with international standards. These enhancements will advance the standardization and refinement of RWD quality regulation in China, ultimately strengthening the scientific rigor and reliability of regulatory decisions.
The hospital information structure, which is made up of various medical business systems, is suffering from the problems of the "information isolated island". Medical business systems in the hospital are mutually isomerous and difficult to become a whole. How to realize the internal barrier-free interaction of the patients effective medical information in the hospital and further to complete the area sharing of patients longitudinal diagnosis and treatment information has become a question having to be solved urgently in the process of healthcare informatization. Based on the HL7 standard, this paper refers to the IHE technical framework, expounds the overall structure of the interaction in the hospital internal and area sharing of medical information with the medical information exchange platform. The paper also gives the details of the whole process of the complete display of the discrete patient health information using Portal technology, which is saved in the business systems in different hospitals. It interacts internally through the information exchange platform and at last stores the information in the regional cinical data repository (CDR).